Descriptive Statistics and you may Images regarding Widely used Terms

We looked at prospective distinctions by webpages, geographical area, and you can ethnicity having fun with t-evaluating and you will research from variance (ANOVA) for the LIWC class percentages. Towards the one or two websites, half a dozen of one’s a dozen t-evaluation was basically extreme regarding the adopting the kinds: first-person only 1 [t(3998) = ?5.61, p Supplementary Desk dos having function, simple deviations, and you will contrasts ranging from cultural groups). Contrasts found tall differences when considering Light and all other cultural teams inside the five of half a dozen high ANOVAs. For this reason, i integrated ethnicity once the a good dummy-coded covariate in the analyses (0 = White, step 1 = Any ethnic groups).

Of twelve ANOVA evaluating linked to geographical area, simply a couple had been tall (members of the family and you may positive emotion). Because variations were not officially important, we don’t believe geographic area inside after that analyses.


Frequency regarding phrase play with goes without saying inside the descriptive statistics (get a hold of Desk step one) and via phrase-clouds. The phrase-cloud approach illustrates the absolute most commonly used terminology over the entire decide to try and also in each one of the age groups. The word-affect system automatically excludes specific terms, in addition to articles (an excellent, and, the) and you will prepositions (in order to, which have, on). The remainder content terminology was scaled in dimensions relative to their regularity, doing an intuitive portrait of the most extremely commonplace content conditions all over this new attempt ( Wordle, 2014).

Figure step one suggests this new 20 most typical stuff words found in the entire shot. As well as get noticed, by far the most frequently used words was indeed like (looking in the 67% out-of users), particularly (looking in the 62% from profiles), appearing (appearing from inside the 55% off pages), and you may individuals (looking inside the fifty% off pages). Ergo, the most common words was comparable all over age groups.

Profile 2 reveals the following 30 most commonly known articles terminology in this new youngest and oldest age range. By detatching the original 20 popular blogs terminology over the decide to try, i train heterogeneity in the matchmaking profiles. In the next 31 words into the youngest age group, high percentage conditions incorporated rating (36% out-of profiles throughout the youngest age group), go (33% off users throughout the youngest age bracket), and you may work (28% out-of users from the youngest age group). In contrast, this new eldest age group had higher proportions off terms and conditions such as travel (31% out of profiles regarding the oldest age group), higher (24% regarding users regarding the eldest age bracket), and you will dating (19% out-of users regarding the earliest age group).

Next 30 typical conditions regarding youngest and eldest decades groups (after subtracting the new 20 common terms away from Profile step one).

Hypothesis Evaluation old Differences in Code within the Matchmaking Pages

To test hypotheses, the brand new portion of terminology regarding the relationships profile that suit for each LIWC category supported since built variables for the regressions. I checked-out many years and you may intercourse because independent parameters as well as modifying for site and you can ethnicity.

Hypothesis step one: Earlier years could be from the increased percentage of terminology throughout the pursuing the groups: first-person plural pronouns, friends, relatives, fitness, and you may confident emotion.

Conclusions mainly supported Hypothesis step one (see Table dos). Five of five regressions found a serious head impact to have decades, in a manner that due to the fact ages of the character publisher increased, the brand new percentage of words regarding group enhanced regarding the following categories: first-individual plural, members of the family, wellness, and you will positive feeling. I discovered no significant decades perception into the proportion of terms and conditions from the loved ones group.

a gender: 0 (female) and step 1 (male). b Site: The two other sites were dictomously coded once the 1 and you can 0. c Ethnicity: 0 (White) and you may step one (Ethnic or racial fraction).

a sex: 0 (female) and step 1 (male). b Website: Both other sites was indeed dictomously coded given that step one and you may 0. c Ethnicity: 0 (White) and you can step 1 (Ethnic or racial minority).